External validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients.

<h4>Background</h4>Readmission prediction models have been developed and validated for targeted in-hospital preventive interventions. We aimed to externally validate the Potentially Avoidable Readmission-Risk Score (PAR-Risk Score), a 12-items prediction model for internal medicine patie...

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Autores principales:	Lukas Higi, Angela Lisibach, Patrick E Beeler, Monika Lutters, Anne-Laure Blanc, Andrea M Burden, Dominik Stämpfli
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6160960cb1214e3c9ea9dda69423d784
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spelling	oai:doaj.org-article:6160960cb1214e3c9ea9dda69423d7842021-12-02T20:16:12ZExternal validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients.1932-620310.1371/journal.pone.0259864https://doaj.org/article/6160960cb1214e3c9ea9dda69423d7842021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0259864https://doaj.org/toc/1932-6203<h4>Background</h4>Readmission prediction models have been developed and validated for targeted in-hospital preventive interventions. We aimed to externally validate the Potentially Avoidable Readmission-Risk Score (PAR-Risk Score), a 12-items prediction model for internal medicine patients with a convenient scoring system, for our local patient cohort.<h4>Methods</h4>A cohort study using electronic health record data from the internal medicine ward of a Swiss tertiary teaching hospital was conducted. The individual PAR-Risk Score values were calculated for each patient. Univariable logistic regression was used to predict potentially avoidable readmissions (PARs), as identified by the SQLape algorithm. For additional analyses, patients were stratified into low, medium, and high risk according to tertiles based on the PAR-Risk Score. Statistical associations between predictor variables and PAR as outcome were assessed using both univariable and multivariable logistic regression.<h4>Results</h4>The final dataset consisted of 5,985 patients. Of these, 340 patients (5.7%) experienced a PAR. The overall PAR-Risk Score showed rather poor discriminatory power (C statistic 0.605, 95%-CI 0.575-0.635). When using stratified groups (low, medium, high), patients in the high-risk group were at statistically significant higher odds (OR 2.63, 95%-CI 1.33-5.18) of being readmitted within 30 days compared to low risk patients. Multivariable logistic regression identified previous admission within six months, anaemia, heart failure, and opioids to be significantly associated with PAR in this patient cohort.<h4>Conclusion</h4>This external validation showed a limited overall performance of the PAR-Risk Score, although higher scores were associated with an increased risk for PAR and patients in the high-risk group were at significantly higher odds of being readmitted within 30 days. This study highlights the importance of externally validating prediction models.Lukas HigiAngela LisibachPatrick E BeelerMonika LuttersAnne-Laure BlancAndrea M BurdenDominik StämpfliPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11, p e0259864 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Lukas Higi Angela Lisibach Patrick E Beeler Monika Lutters Anne-Laure Blanc Andrea M Burden Dominik Stämpfli External validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients.
description	<h4>Background</h4>Readmission prediction models have been developed and validated for targeted in-hospital preventive interventions. We aimed to externally validate the Potentially Avoidable Readmission-Risk Score (PAR-Risk Score), a 12-items prediction model for internal medicine patients with a convenient scoring system, for our local patient cohort.<h4>Methods</h4>A cohort study using electronic health record data from the internal medicine ward of a Swiss tertiary teaching hospital was conducted. The individual PAR-Risk Score values were calculated for each patient. Univariable logistic regression was used to predict potentially avoidable readmissions (PARs), as identified by the SQLape algorithm. For additional analyses, patients were stratified into low, medium, and high risk according to tertiles based on the PAR-Risk Score. Statistical associations between predictor variables and PAR as outcome were assessed using both univariable and multivariable logistic regression.<h4>Results</h4>The final dataset consisted of 5,985 patients. Of these, 340 patients (5.7%) experienced a PAR. The overall PAR-Risk Score showed rather poor discriminatory power (C statistic 0.605, 95%-CI 0.575-0.635). When using stratified groups (low, medium, high), patients in the high-risk group were at statistically significant higher odds (OR 2.63, 95%-CI 1.33-5.18) of being readmitted within 30 days compared to low risk patients. Multivariable logistic regression identified previous admission within six months, anaemia, heart failure, and opioids to be significantly associated with PAR in this patient cohort.<h4>Conclusion</h4>This external validation showed a limited overall performance of the PAR-Risk Score, although higher scores were associated with an increased risk for PAR and patients in the high-risk group were at significantly higher odds of being readmitted within 30 days. This study highlights the importance of externally validating prediction models.
format	article
author	Lukas Higi Angela Lisibach Patrick E Beeler Monika Lutters Anne-Laure Blanc Andrea M Burden Dominik Stämpfli
author_facet	Lukas Higi Angela Lisibach Patrick E Beeler Monika Lutters Anne-Laure Blanc Andrea M Burden Dominik Stämpfli
author_sort	Lukas Higi
title	External validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients.
title_short	External validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients.
title_full	External validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients.
title_fullStr	External validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients.
title_full_unstemmed	External validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients.
title_sort	external validation of the par-risk score to assess potentially avoidable hospital readmission risk in internal medicine patients.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/6160960cb1214e3c9ea9dda69423d784
work_keys_str_mv	AT lukashigi externalvalidationoftheparriskscoretoassesspotentiallyavoidablehospitalreadmissionriskininternalmedicinepatients AT angelalisibach externalvalidationoftheparriskscoretoassesspotentiallyavoidablehospitalreadmissionriskininternalmedicinepatients AT patrickebeeler externalvalidationoftheparriskscoretoassesspotentiallyavoidablehospitalreadmissionriskininternalmedicinepatients AT monikalutters externalvalidationoftheparriskscoretoassesspotentiallyavoidablehospitalreadmissionriskininternalmedicinepatients AT annelaureblanc externalvalidationoftheparriskscoretoassesspotentiallyavoidablehospitalreadmissionriskininternalmedicinepatients AT andreamburden externalvalidationoftheparriskscoretoassesspotentiallyavoidablehospitalreadmissionriskininternalmedicinepatients AT dominikstampfli externalvalidationoftheparriskscoretoassesspotentiallyavoidablehospitalreadmissionriskininternalmedicinepatients
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External validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients.

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